Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/jnPiyush/AgentXWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/jnpiyush/agentx/bug-triage)<a href="https://agentmods.dev/commands/jnpiyush/agentx/bug-triage"><img src="https://agentmods.dev/badge/commands/jnpiyush/agentx/bug-triage/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/jnpiyush/agentx/bug-triage"><img src="https://agentmods.dev/badge/commands/jnpiyush/agentx/bug-triage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.00789 |
| Opus 5.5 | $0.00006 | $0.00316 |
| Sonnet 5.5 | $0.00003 | $0.00158 |
| Haiku 4.5 | $0.00002 | $0.00079 |
Grade A, and why
Bug Triage scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bug Triage Prompt
Context
You are triaging a bug report for Issue #{{issue_number}}.
Instructions
1. Gather Information
From Bug Report:
- Steps to reproduce
- Expected behavior
- Actual behavior
- Environment details
- Screenshots/logs
Additional Information Needed:
- Can it be reproduced consistently?
- What is the affected scope?
- Are there workarounds?
- When did it start occurring?
2. Classify Severity
| Severity | Description | SLA |
|---|---|---|
| Critical | System down, data loss, security breach | 4 hours |
| High | Major feature broken, no workaround | 1 day |
| Medium | Feature broken with workaround | 3 days |
| Low | Minor issue, cosmetic | 1 week |
3. Identify Root Cause Area
Categories:
- Frontend (UI, UX)
- Backend (API, Logic)
- Database (Data, Query)
- Infrastructure (Deploy, Config)
- External (Third-party, Integration)
- Documentation (Docs, Help)
4. Assess Impact
Questions:
- How many users affected?
- Is it blocking production?
- Is there data corruption risk?
- Is there a security implication?
- What is the business impact?
5. Determine Complexity
| Complexity | Description | Typical Effort |
|---|---|---|
| Simple | Typo, config change, obvious fix | < 2 hours |
| Medium | Logic change, single component | 2-8 hours |
| Complex | Multiple components, investigation needed | 1-3 days |
| Major | Architecture change, extensive testing | 3+ days |
6. Routing Decision
Route to:
- Engineer (Direct): Simple bugs, clear fix
- PM: Needs product decision
- Architect: Needs design review
- DevOps: Infrastructure/deployment issue
- Security: Potential vulnerability
7. Output Format
## Bug Triage: Issue #{{issue_number}}
### Classification
- **Severity**: Critical | High | Medium | Low
- **Priority**: P0 | P1 | P2 | P3
- **Category**: [Frontend | Backend | Database | Infra | External]
- **Complexity**: Simple | Medium | Complex | Major
### Impact Assessment
- **Users Affected**: [All | Some | Few]
- **Production Blocking**: Yes | No
- **Data Risk**: Yes | No
- **Security Risk**: Yes | No
### Root Cause Hypothesis
[Brief hypothesis of what's causing the bug]
### Recommended Action
- **Route to**: [Agent/Team]
- **Labels**: [Labels to add]
- **Milestone**: [If applicable]
### Workaround
[If available, describe temporary workaround]
### Additional Context Needed
- [Any missing information needed]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago Changed ec91336d696a
- 1mo ago Changed ddbb3aa22eda
- 1mo ago First seen · 126 lines · 15 tokens per session scan A a56645bcb43c
Bug Triage is a command published in the GitHub repository jnPiyush/AgentX (16 stars, last pushed 3d ago), licensed Apache-2.0. It adds 15 tokens to every session and 789 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-06.
Other commands, from other repositories
bug-report
Draft a bug report issue for lean4-skills.
triage
Query open Node bugs, classify by priority and sub-team, suggest assignments, and generate a triage summary.
speckit.companion.doctor
Report on a spec's run health — unfinished steps, unjournaled tasks, step bleed, drift you can judge, a step that closed having verified nothing, a step that closed without the file it promised, and why completion did not land (read-only, retroactive, never halts).
postmortem
Deliver a structured post-mortem after incidents, mistakes, or stuck sessions. Use when the user requests a structured post-mortem after incidents, mistakes, or stuck sessions.
audit
Audit closed tickets for regressions against today's code (unchanged, evolved, implemented wrong, not implemented), plus duplicate and groupable open ones.
harness:maintenance-pipeline
On-demand, report-first maintenance sweep — runs overdue checks via harness maintenance run, triages findings, and asks the human in plain text before dispatching any fix.